RODRIGO DA SILVA DIAS
Projetos de Pesquisa
Unidades Organizacionais
LIM/21 - Laboratório de Neuroimagem em Psiquiatria, Hospital das Clínicas, Faculdade de Medicina
16 resultados
Resultados de Busca
Agora exibindo 1 - 10 de 16
conferenceObject Increased illness burden in women with co-morbid bipolar and premenstrual dysphoric disorder: data from the large step-BD study(2017) SLYEPCHENKO, A.; FREY, B.; LAFER, B.; NIERENBERG, A. A.; SACHS, G. S.; DIAS, R. S.- Internet use by patients with bipolar disorder: Results from an international multisite survey(2016) BAUER, Rita; CONELL, Joern; GLENN, Tasha; ALDA, Martin; ARDAU, Raffaella; BAUNE, Bernhard T.; BERK, Michael; BERSUDSKY, Yuly; BILDERBECK, Amy; BOCCHETTA, Alberto; BOSSINI, Letizia; CASTRO, Angela M. Paredes; CHEUNG, Eric Y. W.; CHILLOTTI, Caterina; CHOPPIN, Sabine; ZOMPO, Maria Del; DIAS, Rodrigo; DODD, Seetal; DUFFY, Anne; ETAIN, Bruno; FAGIOLINI, Andrea; HERNANDEZ, Miryam Fernandez; GARNHAM, Julie; GEDDES, John; GILDEBRO, Jonas; GONZALEZ-PINTO, Ana; GOODWIN, Guy M.; GROF, Paul; HARIMA, Hirohiko; HASSEL, Stefanie; HENRY, Chantal; HIDALGO-MAZZEI, Diego; KAPUR, Vaisnvy; KUNIGIRI, Girish; LAFER, Beny; LARSEN, Erik R.; LEWITZKA, Ute; LICHT, Rasmus W.; LUND, Anne Hvenegaard; MISIAK, Blazej; MONTEITH, Scott; MUNOZ, Rodrigo; NAKANOTANI, Takako; NIELSEN, Rene E.; O'DONOVAN, Claire; OKAMURA, Yasushi; OSHER, Yamima; PIOTROWSKI, Patryk; REIF, Andreas; RITTER, Philipp; RYBAKOWSKI, Janusz K.; SAGDUYU, Kemal; SAWCHUK, Brett; SCHWARTZ, Elon; SCIPPA, Angela M.; SLANEY, Claire; SULAIMAN, Ahmad H.; SUOMINEN, Kirsi; SUWALSKA, Aleksandra; TAM, Peter; TATEBAYASHI, Yoshitaka; TONDO, Leonardo; VIETA, Eduard; VINBERG, Maj; VISWANATH, Biju; VOLKERT, Julia; ZETIN, Mark; WHYBROW, Peter C.; BAUER, MichaelThere is considerable international interest in online education of patients with bipolar disorder, yet little understanding of how patients use the Internet and other sources to seek information. 1171 patients with a diagnosis of bipolar disorder in 17 countries completed a paper-based, anonymous survey. 81% of the patients used the Internet, a percentage similar to the general public. Older age, less education, and challenges in country telecommunications infrastructure and demographics decreased the odds of using the Internet. About 78% of the Internet users looked online for information on bipolar disorder or 63% of the total sample. More years of education in relation to the country mean, and feeling very confident about managing life decreased the odds of seeking information on bipolar disorder online, while having attended support groups increased the odds. Patients who looked online for information on bipolar disorder consulted medical professionals plus a mean of 2.3 other information sources such as books, physician handouts, and others with bipolar disorder. Patients not using the Internet consulted medical professionals plus a mean of 1.6 other information sources. The percentage of patients with bipolar disorder who use the Internet is about the same as the general public. Other information sources remain important.
- Internet use by older adults with bipolar disorder: international survey results(2018) BAUER, Rita; GLENN, Tasha; STREJILEVICH, Sergio; CONELL, Joern; ALDA, Martin; ARDAU, Raffaella; BAUNE, Bernhard T.; BERK, Michael; BERSUDSKY, Yuly; BILDERBECK, Amy; BOCCHETTA, Alberto; CASTRO, Angela M. Paredes; CHEUNG, Eric Y. W.; CHILLOTTI, Caterina; CHOPPIN, Sabine; CUOMO, Alessandro; ZOMPO, Maria Del; DIAS, Rodrigo; DODD, Seetal; DUFFY, Anne; ETAIN, Bruno; FAGIOLINI, Andrea; HERNANDEZ, Miryam Fernandez; GARNHAM, Julie; GEDDES, John; GILDEBRO, Jonas; GITLIN, Michael J.; GONZALEZ-PINTO, Ana; GOODWIN, Guy M.; GROF, Paul; HARIMA, Hirohiko; HASSEL, Stefanie; HENRY, Chantal; HIDALGO-MAZZEI, Diego; LUND, Anne Hvenegaard; KAPUR, Vaisnvy; KUNIGIRI, Girish; LAFER, Beny; LARSEN, Erik R.; LEWITZKA, Ute; LICHT, Rasmus W.; MISIAK, Blazej; PIOTROWSKI, Patryk; MIRANDA-SCIPPA, Angela; MONTEITH, Scott; MUNOZ, Rodrigo; NAKANOTANI, Takako; NIELSEN, Rene E.; O'DONOVAN, Claire; OKAMURA, Yasushi; OSHER, Yamima; REIF, Andreas; RITTER, Philipp; RYBAKOWSKI, Janusz K.; SAGDUYU, Kemal; SAWCHUK, Brett; SCHWARTZ, Elon; SLANEY, Claire; SULAIMAN, Ahmad H.; SUOMINEN, Kirsi; SUWALSKA, Aleksandra; TAM, Peter; TATEBAYASHI, Yoshitaka; TONDO, Leonardo; VEEH, Julia; VIETA, Eduard; VINBERG, Maj; VISWANATH, Biju; ZETIN, Mark; WHYBROW, Peter C.; BAUER, MichaelBackground: The world population is aging and the number of older adults with bipolar disorder is increasing. Digital technologies are viewed as a framework to improve care of older adults with bipolar disorder. This analysis quantifies Internet use by older adults with bipolar disorder as part of a larger survey project about information seeking. Methods: A paper-based survey about information seeking by patients with bipolar disorder was developed and translated into 12 languages. The survey was anonymous and completed between March 2014 and January 2016 by 1222 patients in 17 countries. All patients were diagnosed by a psychiatrist. General estimating equations were used to account for correlated data. Results: Overall, 47% of older adults (age 60 years or older) used the Internet versus 87% of younger adults (less than 60 years). More education and having symptoms that interfered with regular activities increased the odds of using the Internet, while being age 60 years or older decreased the odds. Data from 187 older adults and 1021 younger adults were included in the analysis excluding missing values. Conclusions: Older adults with bipolar disorder use the Internet much less frequently than younger adults. Many older adults do not use the Internet, and technology tools are suitable for some but not all older adults. As more health services are only available online, and more digital tools are developed, there is concern about growing health disparities based on age. Mental health experts should participate in determining the appropriate role for digital tools for older adults with bipolar disorder.
- Online information seeking by patients with bipolar disorder: results from an international multisite survey(2016) CONELL, Jorn; BAUER, Rita; GLENN, Tasha; ALDA, Martin; ARDAU, Raffaella; BAUNE, Bernhard T.; BERK, Michael; BERSUDSKY, Yuly; BILDERBECK, Amy; BOCCHETTA, Alberto; BOSSINI, Letizia; CASTRO, Angela Marianne Paredes; CHEUNG, Eric Yat Wo; CHILLOTTI, Caterina; CHOPPIN, Sabine; ZOMPO, Maria Del; DIAS, Rodrigo; DODD, Seetal; DUFFY, Anne; ETAIN, Bruno; FAGIOLINI, Andrea; GARNHAM, Julie; GEDDES, John; GILDEBRO, Jonas; GONZALEZ-PINTO, Ana; GOODWIN, Guy M.; GROF, Paul; HARIMA, Hirohiko; HASSEL, Stefanie; HENRY, Chantal; HIDALGO-MAZZEI, Diego; KAPUR, Vaisnvy; KUNIGIRI, Girish; LAFER, Beny; LAM, Chun; LARSEN, Erik Roj; LEWITZKA, Ute; LICHT, Rasmus; LUND, Anne Hvenegaard; MISIAK, Blazej; PIOTROWSKI, Patryk; MONTEITH, Scott; MUNOZ, Rodrigo; NAKANOTANI, Takako; NIELSEN, Rene E.; O'DONOVAN, Claire; OKAMURA, Yasushi; OSHER, Yamima; REIF, Andreas; RITTER, Philipp; RYBAKOWSKI, Janusz K.; SAGDUYU, Kemal; SAWCHUK, Brett; SCHWARTZ, Elon; SCIPPA, Angela Miranda; SLANEY, Claire; SULAIMAN, Ahmad Hatim; SUOMINEN, Kirsi; SUWALSKA, Aleksandra; TAM, Peter; TATEBAYASHI, Yoshitaka; TONDO, Leonardo; VIETA, Eduard; VINBERG, Maj; VISWANATH, Biju; VOLKERT, Julia; ZETIN, Mark; ZORRILLA, Inaki; WHYBROW, Peter C.; BAUER, MichaelBackground: Information seeking is an important coping mechanism for dealing with chronic illness. Despite a growing number of mental health websites, there is little understanding of how patients with bipolar disorder use the Internet to seek information. Methods: A 39 question, paper-based, anonymous survey, translated into 12 languages, was completed by 1222 patients in 17 countries as a convenience sample between March 2014 and January 2016. All patients had a diagnosis of bipolar disorder from a psychiatrist. Data were analyzed using descriptive statistics and generalized estimating equations to account for correlated data. Results: 976 (81 % of 1212 valid responses) of the patients used the Internet, and of these 750 (77 %) looked for information on bipolar disorder. When looking online for information, 89 % used a computer rather than a smartphone, and 79 % started with a general search engine. The primary reasons for searching were drug side effects (51 %), to learn anonymously (43 %), and for help coping (39 %). About 1/3 rated their search skills as expert, and 2/3 as basic or intermediate. 59 % preferred a website on mental illness and 33 % preferred Wikipedia. Only 20 % read or participated in online support groups. Most patients (62 %) searched a couple times a year. Online information seeking helped about 2/3 to cope (41 % of the entire sample). About 2/3 did not discuss Internet findings with their doctor. Conclusion: Online information seeking helps many patients to cope although alternative information sources remain important. Most patients do not discuss Internet findings with their doctor, and concern remains about the quality of online information especially related to prescription drugs. Patients may not rate search skills accurately, and may not understand limitations of online privacy. More patient education about online information searching is needed and physicians should recommend a few high quality websites.
conferenceObject Premenstrual mood symptoms after menarche association with early onset and perinatal mood disorders in women with bipolar disorder - fidings from STEP-BD(2015) DIAS, R.; LAFER, B.; SACHS, G. S.; NIERENBERG, A. A.; JOFFE, H.conferenceObject 6 Citação(ões) na Scopus Forecasting depressive relapse in Bipolar Disorder from clinical data(2018) BORGES-JUNIOR, Renato; SALVINI, Rogerio; NIERENBERG, Andrew A.; SACHS, Gary S.; LAFER, Beny; DIAS, Rodrigo S.Bipolar disorder (BD) is a mood disorder characterized by recurrent episodes of depression and mania/hypomania. Depressive relapse in BD reach rates close to 50% in 1 year and 70% in up to 4 years of treatment. Several studies have been developed to discover more efficient treatments for BD and prevent relapses. However, most of relapse studies used only statistical methods. We aim to analyze the performance of machine learning algorithms in predicting depressive relapse using only clinical data from patients. Five well-used machine learning algorithms (Support Vector Machines, Random Forests, Naive Bayes and Multilayer Perceptron) were applied to the Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) dataset of a cohort of 800 patients who became euthymic during the study and were followed up for 1 year: 507 presented a depressive relapse and 293 did not. The algorithms showed reasonable performance in the prediction task, ranging from 61% to 80% in the F-measure. Random Forest algorithm had a higher average of performance (Relapse Group 68%; No Relapse Group 74%), although, the performance between classifiers showed no significant difference. Random Forest analysis demonstrated that the three most important mood symptoms observed were: interest, depression mood and energy. Results show that the machine learning algorithms could be seen as a sensible approach to better support medical decision-making in the BD treatment and prevention of future relapses.conferenceObject Bipolar disorder and premenstrual disphoric disorder comorbidity: Apriori algorithm study(2018) DIAS, R.; CASTRO, G.; SALVINI, R.; SLYEPCHENKO, A.; ANDREW, A. A.; SACHS, G. S.; LAFER, B.; DIAS, R. S.- Online information seeking by patients with bipolar disorder: results from an international multisite survey (vol 4, pg 1, 2016)(2017) CONELL, Jorn; BAUER, Rita; GLENN, Tasha; ALDA, Martin; ARDAU, Raffaella; BAUNE, Bernhard T.; BERK, Michael; BERSUDSKY, Yuly; BILDERBECK, Amy; BOCCHETTA, Alberto; BOSSINI, Letizia; CASTRO, Angela Marianne Paredes; CHEUNG, Eric Yat Wo; CHILLOTTI, Caterina; CHOPPIN, Sabine; ZOMPO, Maria Del; DIAS, Rodrigo; DODD, Seetal; DUFFY, Anne; ETAIN, Bruno; FAGIOLINI, Andrea; GARNHAM, Julie; GEDDES, John; GILDEBRO, Jonas; GONZALEZ-PINTO, Ana; GOODWIN, Guy M.; GROF, Paul; HARIMA, Hirohiko; HASSEL, Stefanie; HENRY, Chantal; HIDALGO-MAZZEI, Diego; KAPUR, Vaisnvy; KUNIGIRI, Girish; LAFER, Beny; LAM, Chun; LARSEN, Erik Roj; LEWITZKA, Ute; LICHT, Rasmus; LUND, Anne Hvenegaard; MISIAK, Blazej; PIOTROWSKI, Patryk; MONTEITH, Scott; MUNOZ, Rodrigo; NAKANOTANI, Takako; NIELSEN, Rene E.; O'DONOVAN, Claire; OKAMURA, Yasushi; OSHER, Yamima; REIF, Andreas; RITTER, Philipp; RYBAKOWSKI, Janusz K.; SAGDUYU, Kemal; SAWCHUK, Brett; SCHWARTZ, Elon; SCIPPA, Angela Miranda; SLANEY, Claire; SULAIMAN, Ahmad Hatim; SUOMINEN, Kirsi; SUWALSKA, Aleksandra; TAM, Peter; TATEBAYASHI, Yoshitaka; TONDO, Leonardo; VIETA, Eduard; VINBERG, Maj; VISWANATH, Biju; VOLKERT, Julia; ZETIN, Mark; ZORRILLA, Inaki; WHYBROW, Peter C.; BAUER, Michael
- Applying association rules to study Bipolar Disorder and Premenstrual Dysphoric Disorder comorbidity(2018) CASTRO, Giovanna; SALVINI, Rogerio; SOARES, Fabrizzio A. A. M. N.; NIERENBERG, Andrew A.; SACHS, Gary S.; LAFER, Beny; DIAS, Rodrigo S.Bipolar Disorder (BD) is characterized by mood changes that manifest as depressive episodes alternating with episodes of euphoria, in varying degrees of intensity. Women with BD may experience worsening symptoms during events of their reproductive life, particularly those suffering from Premenstrual Dysphoric Disorder (PMDD). The presence of PMDD in the diagnoses of BD is considered a marker of severity for the disease. In this study, data from a cohort of 1099 women with BD were used for an exploratory analysis using association rules in order to find associations between PMDD and BD symptoms. Of the thousands of generated rules, those that have associations with PMDD were selected and categorized, with confidence levels between 70% and 100%.
conferenceObject Applying machine learning to predict depression relapse of bipolar disorder patients(2018) DIAS, R.; BORGES-JUNIOR, R. Gomes; SALVINI, R.; CAMILO-JUNIOR, C. Goncalves; LAFER, B.; NIERENBERG, A. A.; SACHS, G. S.